Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

Mitigating the Effects of Climate Change on the Water Resources of the Columbia River Basin

The potential effects of climate change on the hydrology and water resources of the Columbia River Basin (CRB) were evaluated using simulations from the U.S. Department of Energy and National Center for Atmospheric Research Parallel Climate Model (DOE/NCAR PCM). This study focuses on three climate projections for the 21st century based on a `business as usual' (BAU) global emissions scenario, evaluated with respect to a control climate scenario based on static 1995 emissions. Time-varying monthly PCM temperature and precipitation changes were statistically downscaled and temporally disaggregated to produce daily forcings that drove a macro-scale hydrologic simulation model of the Columbia River basin at 1/4-degree spatial resolution. For comparison with the direct statistical downscaling approach, a dynamical downscaling approach using a regional climate model (RCM) was also used to derive hydrologic model forcings for 20-year subsets from the PCM control climate (1995–2015) scenario and from the three BAU climate(2040–2060) projections. The statistically downscaled PCM scenario results were assessed for three analysis periods (denoted Periods 1–3: 2010–2039,2040–2069, 2070–2098) in which changes in annual average temperature were +0.5,+1.3 and +2.1 °C, respectively, while critical winter season precipitation changes were –3, +5 and +1 percent. For RCM, the predicted temperature change for the 2040–2060 period was +1.2 °C and the average winter precipitation change was –3 percent, relative to the RCM controlclimate. Due to the modest changes in winter precipitation, temperature changes dominated the simulated hydrologic effects by reducing winter snow accumulation, thus shifting summer streamflow to the winter. The hydrologic changes caused increased competition for reservoir storage between firm hydropower and instream flow targets developed pursuant to the Endangered Species Act listing of Columbia River salmonids. We examined several alternative reservoir operating policies designed to mitigate reservoir system performance losses. In general, the combination of earlier reservoir refill with greater storage allocations for instream flow targets mitigated some of the negative impacts to flow, but only with significant losses in firm hydropower production (ranging from –9 percent in Period1 to –35 percent for RCM). Simulated hydropower revenue changes were lessthan 5 percent for all scenarios, however, primarily due to small changes inannual runoff.     

Climate Changes in the 21st Century over the Asia-Pacific Region Simulated by the NCAR CSM and PCM

The Climate System Model (CSM) and the Parallel Climate Model (PCM), two coupled global climate models without flux adjustments recently developed at NCAR, were used to simulate the 20th century climate using historical greenhouse gas and sulfate aerosol forcing. These simulations were extended through the 21st century under two newly developed scenarios, a business-as-usual case (BAU, CO2≈710 ppmv in 2100) and a CO2 stabilization case (STA550, CO2≈540 ppmv in 2100). The simulated changes in temperature, precipitation, and soil moisture over the Asia-Pacific region (10°-60°N, 55°-155°E) are analyzed, with a focus on the East Asian summer monsoon rainfall and climate changes over the upper reaches of the Yangtze River. Under the BAU scenario, both the models produce surface warming of about 3-5℃ in winter and 2-3℃ in summer over most Asia. Under the STA550 scenario, the warming is reduced by 0.5-1.0℃ in winter and by 0.5℃ in summer. The warming is fairly uniform at the low latitudes and does not induce significant changes in the zonal mean Hadley circulation over the Asia-Pacific do main. While the regional precipitation changes from single CSM integrations are noisy, the PCM ensemble mean precipitation shows 10%-30% increases north of ～ 30°N and ～ 10% decreases south of ～ 30°N over the Asia-Pacific region in winter and 10%-20% increases in summer precipitation over most of the region. Soil moisture changes are small over most Asia. The CSM single simulation suggests a 30% increase in river runoff into the Three Gorges Dam, but the PCM ensemble simulations show small changes in the runoff.     

U.S. Climate Sensitivity Simulated with the NCEP Regional Spectral Model

10-year continuous U.S. climate simulations were conducted with the Regional Spectral Model (RSM) using boundary conditions from the National Centers for Environmental Prediction/Dept. of Energy reanalyses and the global PCM (Parallel Climate Model) simulations for present day (1986–1996) andfuture (2040–2050) CO₂ concentrations (about a 36% increasedCO₂). In order to examine the influence of physical parameterization differences as well as grid-resolution, fine resolution RSM simulations (50 km) were compared to coarse resolution (180 and 250 km) RSM simulations, which had resolutions comparable to the T62 reanalysis and PCM simulations. During the winter, the fine resolution RSM simulations provided more realistic detail over the western mountains. During the summer, large differences between the RSM and driving PCM simulations were found. Our results with presentCO₂ suggest that most of the differences between the regionalclimate model simulations and the climate simulations driven by the global model used to drive the regional climate model were not due to the finer resolution of the regional climate model but to the different treatment of the physical processes in the two models, especially when the subgrid scale physics was important, like during summer. Compared to the coarse resolution RSM simulation results, on the other hand, the fine resolution RSM simulations did show improved simulation skills especially when a good boundary condition such as the reanalysis was used to drive the RSM. Under increased CO₂, the driving PCM and downscaled RSM simulations exhibitedwarming over all vertical layers and all regions. Both the RSM and PCM had increased precipitation during the winter, but during the summer, the PCM simulation had an overall precipitation increase mainly due to increased subgrid scale convective activity, whereas the RSM simulations exhibited precipitation decreases and the resulting RSM soil moisture became dryer, especially in the U.S. Southwest. Most of differences in the simulated climate change signals were produced by the distinct model physics rather than by differences in grid resolution.     

Potential Implications of PCM Climate Change Scenarios for Sacramento–San Joaquin River Basin Hydrology and Water Resources

The potential effects of climate change on the hydrology and water resources of the Sacramento–San Joaquin River Basin were evaluated using ensemble climate simulations generated by the U.S. Department of Energy and National Center for Atmospheric Research Parallel Climate Model (DOE/NCAR PCM). Five PCM scenarios were employed. The first three were ensemble runs from 1995–2099 with a `business as usual' global emissions scenario, eachwith different atmospheric initializations. The fourth was a `control climate'scenario with greenhouse gas emissions set at 1995 levels and run through 2099. The fifth was a historical climate simulation forced with evolving greenhouse gas concentrations from 1870–2000, from which a 50-yearportion is taken for use in bias-correction of the other runs. From these global simulations, transient monthly temperature and precipitation sequences were statistically downscaled to produce continuous daily hydrologic model forcings, which drove a macro-scale hydrology model of theSacramento–San Joaquin River Basins at a 1/8-degree spatial resolution, and produceddaily streamflow sequences for each climate scenario. Each streamflow scenario was used in a water resources system model that simulated current and predicted future performance of the system. The progressive warming of the PCM scenarios (approximately 1.2 °C at midcentury, and 2.2 °C by the 2090s), coupled with reductions in winter and spring precipitation (from 10 to 25%), markedly reduced late spring snowpack (by as much as half on average by the end of the century). Progressive reductions in winter, spring, and summer streamflow were less severe in the northern part of the study domain than in the south, where a seasonality shift was apparent. Results from the water resources system model indicate that achieving and maintaining status quo (control scenario climate) system performance in the future would be nearly impossible, given the altered climate scenario hydrologies. The most comprehensive of the mitigation alternatives examined satisfied only 87–96% of environmental targets in the Sacramento system, and less than 80% in the San Joaquin system. It is evident that demand modification and system infrastructure improvements will be required to account for the volumetric and temporal shifts in flows predicted to occur with future climates in the Sacramento–San JoaquinRiver basins.     

Evaluation of Hydrologically Relevant PCM Climate Variables and Large-Scale Variability over the Continental U.S.

The ability of the Parallel Climate Model (PCM) to reproduce the mean and variability of hydrologically relevant climate variables was evaluated by comparing PCM historical climate runs with observations over temporal scales from sub-daily to annual. The domain was the continental U.S, and the model spatial resolution was T42 (about 2.8 degrees latitude by longitude). The climate variables evaluated include precipitation, surface air temperature, net surface solar radiation, soil moisture, and snow water equivalent. The results show that PCM has a winter dry bias in the Pacific Northwest and a summer wet bias in the central plains. The diurnal precipitation variation in summer is much stronger than observed, with an afternoon maximum in summer precipitation over much of the U.S. interior, in contrast with an observed nocturnal maximum in parts of the interior. PCM has a cold bias in annual mean temperature over most of the U.S., with deviations as large as ?8 K. The PCM daily temperature range is lower than observed, especiallyin the central U.S. PCM generally overestimates the net solar radiation over most of the U.S, although the diurnal cycle is simulated well in spring, summer and winter. In autumn PCM has a pronounced noontime peak in solar radiation that differs by 5–10% from observations. PCM'ssimulated soil moisture is less variable than that of a sophisticated land-surface hydrology model, especially in the interior of the country. PCM simulates the wetter conditions over the southeastern U.S. and California during warm (El Niño) events, but shifts the drier conditions in the PacificNorthwest northward and underestimates their magnitude. The temperature response to the North Pacific Oscillation is generally captured by PCM, but the amplitude of this response is overestimated by a factor of about two.     

未来气候变化对黄河流域水文过程的影响

使用NASA/NCAR有限区域大气环流模型FvGCM结果驱动高分辨率区域气候模式RegCM3 (20 km),进行1961～1990年当代气候模拟(控制试验)和2071～2100年IPCC A2排放情景下未来气候模拟(A2情景模拟试验)。将RegCM3径流模拟结果同大尺度汇流模型LRM [分辨率0.25°(纬度)×0.25°(经度)]相连接,模拟预估未来气候变化对我国黄河流域水文过程的影响。结果表明:相对于当代气候,未来黄河流域呈现气温升高、降水增加(夏季7～8月降水减少)和蒸发增大的趋势,且空间分布极不均匀,造成河川径流在5～10月减少,加剧流域夏季的水资源短缺;未来气温升高使得融雪径流增加,可能导致更早和更大的春季径流,使径流过程发生季节性迁移,引起黄河流域水资源年内分配发生变化。     

青藏高原东西部积雪效应的模拟对比分析

采用引入次网格尺度地形重力波拖曳的NCAR区域气候模式(RegCM2),以SMMR微波逐候积雪深度观测值为依据,加入较合理的积雪强迫,通过数值模拟,研究了青藏高原(下称高原)东、西部积雪异常对后期区域环流的不同影响。模拟结果的对比分析表明,高原西部多雪对高原东部积雪存在正的反馈作用,有利于高原东部积雪的增加,而高原东部多雪对高原西部积雪的影响很小。高原西部积雪偏多和高原东部积雪偏多对后期大气温度场和高度场的影响具有基本相同的分布形态,只是影响强度有所不同。高原西部积雪的融化要迟于高原东部积雪,高原西部积雪效应的持续性较强。另外,高原西部多雪对高原东部积雪存在正的反馈作用,高原东部积雪的增加进一步加大了整个高原积雪的异常,因此,高原西部积雪偏多对后期环流的综合影响明显大于高原东部积雪偏多的影响。     

Impacts of global warming on hydrological cycles in the Asian monsoon region

The hydrologic changes and the impact of these changes constitute a fundamental global-warmingrelated concern. Faced with threats to human life and natural ecosystems, such as droughts, floods, and soil erosion, water resource planners must increasingly make future risk assessments. Though hydrological predictions associated with the global climate change are already being performed, mainly through the use of GCMs, coarse spatial resolutions and uncertain physical processes limit the representation of terrestrial water/energy interactions and the variability in such systems as the Asian monsoon. Despite numerous studies, the regional responses of hydrologic changes resulting from climate change remains inconclusive. In this paper, an attempt at dynamical downsealing of future hydrologic projection under global climate change in Asia is addressed. The authors conducted present and future Asian regional climate simulations which were nested in the results of Atmospheric General Circulation Model （AGCM） experiments. The regional climate model could capture the general simulated features of the AGCM. Also, some regional phenomena such as orographic precipitation, which did not appear in the outcome of the AGCM simulation, were successfully produced. Under global warming, the increase of water vapor associated with the warmed air temperature was projected. It was projected to bring more abundant water vapor to the southern portions of India and the Bay of Bengal, and to enhance precipitation especially over the mountainous regions, the western part of India and the southern edge of the Tibetan Plateau. As a result of the changes in the synoptic flow patterns and precipitation under global warming, the increases of annual mean precipitation and surface runoff were projected in many regions of Asia. However, both the positive and negative changes of seasonal surface runoff were projected in some regions which will increase the flood risk and cause a mismatch between water demand and water availability in the agricul     

A regional climate model for the western United States

A numerical approach to modeling climate on a regional scale is developed whereby large-scale weather systems are simulated with a global climate model (GCM) and the GCM output is used to provide the boundary conditions needed for high-resolution mesoscale model simulations over the region of interest. In our example, we use the National Center for Atmospheric Research (NCAR) community climate model (CCM1) and the Pennsylvania State University (PSU)/NCAR Mesoscale Model version 4 (MM4) to apply this approach over the western United States (U.S.). The topography, as resolved by the 500-km mesh of the CCM1, is necessarily highly distorted, but with the 60-km mesh of the MM4 the major mountain ranges are distinguished. To obtain adequate and consistent representations of surface climate, we use the same radiation and land surface treatments in both models, the latter being the recently developed Biosphere-Atmosphere Transfer Scheme (BATS). Our analysis emphasizes the simulation at four CCM1 points surrounding Yucca Mountain, NV, because of the need to determine its climatology prior to certification as a high-level nuclear waste repository.We simulate global climate for three years with CCM1/BATS and describe the resulting January surface climatology over the western U.S. The details of the precipitation patterns are unrealistic because of the smooth topography. Selecting five January CCM1 storms that occur over the western U.S. with a total duration of 20 days for simulation with the MM4, we demonstrate that the mesoscale model provides much improved wintertime precipitation patterns. The storms in MM4 are individually much more realistic than those in CCM1. A simple averaging procedure that infers a mean January rainfall climatology calculated from the 20 days of MM4 simulation is much closer to the observed than is the CCM1 climatology. The soil moisture and subsurface drainage simulated over 3–5 day integration periods of MM4, however, remain strongly dependent on the initial CCM1 soil moisture and thus are less realistic than the rainfall. Adequate simulation of surface soil water may require integrations of the mesoscale model over time periods.The National Center for Atmospheric Research is sponsored by the National Science Foundation. of up to several months or longer.     

Modeling the transport of nutrients and sediment loads into Lake Tahoe under projected climatic changes

The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.     

Parametrization schemes of incident radiation in the North Water polynya

Abstract

An evaluation of the Canadian Land Surface Scheme (CLASS) 3.1 snow cover simulations at four sites included in the Snow Model Intercomparison Project (SnowMIP) revealed that CLASS was able to provide realistic representations of snow cover accumulation, melt and physical properties over a range of snow cover climates. The modified snow aging parametrization in CLASS 3.1 provided improved simulations of snowpack density which resulted in a marked reduction in the root‐mean‐square (rms) error for daily snow depth, and slight improvements in snow surface temperature. CLASS 3.1 still exhibited a tendency to overestimate snow cover duration which is attributed to the way shallow snow ablation is treated. CLASS provided generally realistic simulations of daily and seasonal variation in snow albedo although cold snow albedo was underpredicted by 0.10 to 0.15 at a site with a deep (> 2 m) cold snowpack. CLASS also exhibited a tendency to overpredict late spring snow albedo which was reduced by the addition of a snow layer subroutine that kept track of snow albedo by precipitation event. CLASS had a noticeable cold bias averaging 3°–4°C at two mountain sites included in the comparison. The bias was closely linked to atmospheric stability and could exceed 10°C under conditions of strong radiative cooling and low wind speeds. The CLASS energy deficit under these conditions was determined to be ～20–40 W m^?2 and was mostly accounted for by introducing a windless exchange coefficient into the calculation of sensible heat fluxes following the approach used in a number of other physical snowpack models. CLASS provided realistic simulations of daily snowmelt runoff with the exception of the Weissfluhjoch site which was characterized by a deep cold snowpack. A preliminary assessment of snow water equivalent (SWE) rms error for the 23 models participating in SnowMIP showed that CLASS was one of the better single layer snow models included in the comparison. CLASS performance was comparable to the multi‐layer CROCUS snowpack model in the evaluations carried out in this study.     

Hydrologic effects of climate change in the Yukon River Basin

A monthly water balance (WB) model was developed for the Yukon River Basin (YRB). The WB model was calibrated using mean monthly values of precipitation and temperature derived from the Precipitation-elevation Regression on Independent Slopes Model (PRISM) data set and by comparing estimated mean monthly runoff with runoff measured at Pilot Station, Alaska. The calibration procedure used the Shuffled Complex Evolution global search. Potential hydrologic effects of climate change were assessed for the YRB by imposing changes in precipitation and temperature derived from selected Inter-governmental Panel for Climate Change (IPCC) climate simulations. Scenarios from five general circulation model (GCM) simulations were used to provide a range of potential changes. Results from the scenarios indicate an increase in annual runoff in the twenty-first century for the YRB with simulated increases in precipitation having the greatest effect on increases in runoff. Simulated increases in temperature were found to alter the timing of snow accumulation and melt.     

Preliminary Assessment of Simulations of Climate Changes over China by CMIP5 Multi-Models

Based on 18 global climate models’ simulations of the 20th century climate, a set of experiments within phase five of the Coupled Model Inter-comparison Project (CMIP5), the performances of simulating the present climate over China are assessed. Compared with observations, models can capture the dominant features of the geographic distributions of temperature and precipitation during 1961-2005. For the temporal changes of temperature, models appear to have a good performance on reproducing the warming tendency but show limited skills for precipitation. For the regional mean temperature and precipitation over the whole of China, most models underestimate the actual temperature and overestimate precipitation. Concerning the standard deviations of simulations by the 18 models, they are larger for temperature in the western part of China, while the standard deviations are larger for precipitation in the South.     

The Effects of Climate Change on the Hydrology and Water Resources of the Colorado River Basin

The potential effects of climate change on the hydrology and water resources of the Colorado River basin are assessed by comparing simulated hydrologic and water resources scenarios derived from downscaled climate simulations of the U.S. Department of Energy/National Center for Atmospheric Research Parallel Climate Model (PCM) to scenarios driven by observed historical (1950–1999) climate. PCM climate scenarios include an ensemble of three 105-year future climate simulations based on projected `business-as-usual'(BAU) greenhouse gas emissions and a control climate simulation based on static 1995 greenhouse gas concentrations. Downscaled transient temperature and precipitation sequences were extracted from PCM simulations, and were used to drive the Variable Infiltration Capacity (VIC) macroscale hydrology model to produce corresponding streamflow sequences. Results for the BAU scenarios were summarized into Periods 1, 2, and 3 (2010–2039,2040–2069, 2070–2098). Average annual temperature changes for the Colorado Riverbasin were 0.5 °C warmer for control climate, and 1.0, 1.7, and 2.4 °C warmer for Periods 1–3, respectively, relative to the historicalclimate. Basin-average annual precipitation for the control climate was slightly(1%) less than for observed historical climate, and 3, 6, and 3%less for future Periods 1–3, respectively. Annual runoff in the controlrun was about 10% lower than for simulated historical conditions, and 14, 18, and 17% less for Periods 1–3, respectively. Analysis of watermanagement operations using a water management model driven by simulated streamflows showed that streamflows associated with control and future BAU climates would significantly degrade the performance of the water resourcessystem relative to historical conditions, with average total basin storage reduced by 7% for the control climate and 36, 32 and 40% for Periods 1–3, respectively. Releases from Glen Canyon Dam to the LowerBasin (mandated by the Colorado River Compact) were met in 80% of years for the control climate simulation (versus 92% in the historical climate simulation), and only in 59–75% of years for the future climate runs. Annual hydropower output was also significantly reduced for the control and future climate simulations. The high sensitivity of reservoir system performance for future climate is a reflection of the fragile equilibrium that now exists in operation of the system, with system demands only slightly less than long-term mean annual inflow.     

Present-day and future precipitation in the Baltic Sea region as simulated in a suite of regional climate models

Here we investigate simulated changes in the precipitation climate over the Baltic Sea and surrounding land areas for the period 2071–2100 as compared to 1961–1990. We analyze precipitation in 10 regional climate models taking part in the European PRUDENCE project. Forced by the same global driving climate model, the mean of the regional climate model simulations captures the observed climatological precipitation over the Baltic Sea runoff land area to within 15% in each month, while single regional models have errors up to 25%. In the future climate, the precipitation is projected to increase in the Baltic Sea area, especially during winter. During summer increased precipitation in the north is contrasted with a decrease in the south of this region. Over the Baltic Sea itself the future change in the seasonal cycle of precipitation is markedly different in the regional climate model simulations. We show that the sea surface temperatures have a profound impact on the simulated hydrological cycle over the Baltic Sea. The driving global climate model used in the common experiment projects a very strong regional increase in summertime sea surface temperature, leading to a significant increase in precipitation. In addition to the common experiment some regional models have been forced by either a different set of Baltic Sea surface temperatures, lateral boundary conditions from another global climate model, a different emission scenario, or different initial conditions. We make use of the large number of experiments in the PRUDENCE project, providing an ensemble consisting of more than 25 realizations of climate change, to illustrate sources of uncertainties in climate change projections.     

A subgrid parameterization of orographic precipitation

Summary Estimates of the impact of global climate change on land surface hydrology require climate information on spatial scales far smaller than those explicitly resolved by global climate models of today and the foreseeable future. To bridge the gap between what is required and what is resolved, we propose a subgrid-scale parameterization of the influence of topography on clouds, precipitation, and land surface hydrology. The parameterization represents subgrid variations in surface elevation in terms of probability distributions of discrete elevation classes. Separate cloud, radiative, and surface processes are calculated for each elevation class. Rainshadow effects are not treated by the parameterization; they have to be explicitly resolved by the host model. The simulated surface temperature, precipitation, and snow cover for each elevation class are distributed to different geographical locations according to the spatial distribution of surface elevation within each grid cell.The subgrid parameterization has been implemented in the Pacific Northwest Laboratory's climate version of the Penn State/NCAR Mesoscale Model. The scheme is evaluated by driving the regional climate model with observed lateral boundary conditions for the Pacific Northwest and comparing simulated fields with surface observations. The method yields more realistic spatial distributions of precipitation and snow cover in mountainous areas and is considerably more computationally efficient than achieving high resolution by the use of nesting in the regional climate model.With 17 Figures     

Effects of subgrid heterogeneities in soil infiltration capacity and precipitation on regional climate: a sensitivity study

Summary ?One of the most pronounced features of the land surface is its heterogeneity. In order to further understand land-atmosphere interactions and improve climate modeling it is very important to investigate effects of subgrid scale heterogeneities, especially hydrological-process heterogeneities. In this paper, after the construction and sensitivity tests of a hydrological model (VXM), which accounts for precipitation heterogeneity (PH) and infiltration heterogeneity (IH), we incorporated VXM into the NCAR (National Center for Atmospheric Research) regional climate model RegCM2 and thus obtained the augmented regional climate model (hereafter, ARCM). By using 3-month (May–July) observational data of 1991 Meiyu season, we conducted numerical experiments with ARCM, analyzed the sensitivities, and found that: (1) The regional climate and surface hydrology are very sensitive to IH as well as PH, i.e., the simulations for the surface fluxes, soil temperature, soil moisture, precipitation and surface runoff can be greatly affected by those heterogeneities. (2) ARCM can effectively improve the simulation of hydrological processes, i.e., it can greatly enhance the surface runoff ratio (i.e., the ratio of surface runoff to precipitation), which is consistent with observations over humid areas in China. (3) It seems that the IH influence on the surface climate is larger than the PH influence. (4) The modeled climate is sensitive to the VXM parameters. For example, it is significantly modified after the surface impermeable fraction has been accounted for, suggesting some features of aridification. Received June 18, 2001; revised February 14, 2002; accepted March 3, 2002     

Trends of Regional Precipitation and Their Control Mechanisms during 1979–2013

Trends in precipitation are critical to water resources. Considerable uncertainty remains concerning the trends of regional precipitation in response to global warming and their controlling mechanisms. Here, we use an interannual difference method to derive trends of regional precipitation from GPCP(Global Precipitation Climatology Project) data and MERRA(ModernEra Retrospective Analysis for Research and Applications) reanalysis in the near-global domain of 60?S–60?N during a major global warming period of 1979–2013. We find that trends of regional annual precipitation are primarily driven by changes in the top 30% heavy precipitation events, which in turn are controlled by changes in precipitable water in response to global warming, i.e., by thermodynamic processes. Significant drying trends are found in most parts of the U.S. and eastern Canada,the Middle East, and eastern South America, while significant increases in precipitation occur in northern Australia, southern Africa, western India and western China. In addition, as the climate warms there are extensive enhancements and expansions of the three major tropical precipitation centers–the Maritime Continent, Central America, and tropical Africa–leading to the observed widening of Hadley cells and a significant strengthening of the global hydrological cycle.     

Causes of recent changes in western North American snowpack

Monthly snow water equivalent (SWE) station observations and gridded temperature data are used to identify mechanisms by which warming affects the temporal and geographical structure of changes in western North American mountain snowpack. We first exploit interannual variability to demonstrate the sensitivity of snowpack to temperature during the various phases of the snow season. We show that mechanisms whereby temperature affects snowpack emerge in the mid to late portion of the snow season (March through May), but are nearly absent during the earliest phase (February), when temperatures are generally well below freezing. The mid to late snow season is precisely when significant loss of snowpack is seen at nearly all locations over the past few decades, both through decreases in snow accumulation and increases in snowmelt. At locations where April 1st SWE has been increasing over the past few decades, the increase is entirely due to a significant enhancement of accumulation during the earliest phase of the snow season, when the sensitivity analysis indicates that temperature is not expected to affect snowpack. Later in the snow season, these stations exhibit significant snowpack loss comparable to the other stations. Based on this analysis, it is difficult to escape the conclusion that recent snowpack changes in western North America are caused by regional-scale warming. Given predictions of future warming, a further reduction in late season snowpack and advancement in the onset of snowmelt should be expected in the coming decades throughout the region.